The method of analyzing social mobility described by Fox (1990) is flawed in its adjustment for between-group differences in destination status when estimating the extent of the mentally ill's mobility as compared with the general population. Use of the recommended model with hypothetical data sets resulted in a significant finding when no overall upward or downward mobility occurred, and a non-significant result when the downward mobility of a psychotic group was contrived to be massive. An alternative model for the test of group differences in mobility is suggested within the framework of log-linear analysis commended by Fox (1990). This method indicated significantly more downward and less upward mobility in mentally ill groups when data from four studies were re-analyzed. We conclude that the weight of evidence from published studies supports the notion of social selection-drift, although this does not imply the inconsequence of social factors in the aetiology of schizophrenia (and other psychoses) or in its prognosis and occupational consequences.
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Syst Rev
January 2025
Division of Epidemiology & Biostatistics, School of Public Health, University of Cape Town, Cape Town, South Africa.
Introduction: Human mobility is associated with an increased risk of HIV acquisition and disengagement from HIV care, leading to poorer health outcomes among highly mobile individuals compared to less mobile individuals. Mobile individuals, broadly defined as those who temporally, seasonally, or permanently move from one place to another for voluntary or involuntary reasons, face many challenges in accessing HIV care services. These challenges include logistical difficulties, interruptions in HIV care continuity, and limited access to services across different locations, which together hinder timely testing, treatment initiation, and viral suppression.
View Article and Find Full Text PDFBackground: An increasing number of older people are being treated in German hospitals. In 2022, more than 35.7 million hospitalized patients in Germany were of age 65 or older.
View Article and Find Full Text PDFBiomater Transl
November 2024
Organoid Research Center, Institute of Translational Medicine, Shanghai University, Shanghai, China.
The skeletal system, composed of bones, muscles, joints, ligaments, and tendons, serves as the foundation for maintaining human posture, mobility, and overall biomechanical functionality. However, with ageing, chronic overuse, and acute injuries, conditions such as osteoarthritis, intervertebral disc degeneration, muscle atrophy, and ligament or tendon tears have become increasingly prevalent and pose serious clinical challenges. These disorders not only result in pain, functional loss, and a marked reduction in patients' quality of life but also impose substantial social and economic burdens.
View Article and Find Full Text PDFSSM Popul Health
March 2025
Department of Sociology, Purdue University, United States.
Although socioeconomic status is salient for health and well-being across the life course, previous research indicates that the social gradient in health is racialized and that Black adults experience diminishing health returns on higher socioeconomic status. We extend this literature by examining whether there are diminishing physiological health returns on intergenerational mobility groups for Black adults and, if so, whether diminishing health returns vary across age. We use six waves of data from the Health and Retirement Study (N = 11,846) and mixed effects models; and average marginal effects are used to interpret the race by intergenerational mobility interaction.
View Article and Find Full Text PDFSci Rep
January 2025
School of Economics and Management, University of Cyprus, 2109, Aglantzia, Nicosia, Cyprus.
Analyzing the habits of exercisers is crucial for developing targeted interventions that can effectively promote long-term physical activity behavior. While much of existing literature has focused on individual-level factors, there is a growing recognition of the importance of examining how broader determinants impact physical activity. In this study, we analyze large-scale human mobility data from over 20 million individuals to investigate how visits to various locations, such as cafes and restaurants, influence visits to fitness centers.
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